Have Medical Care prices risen faster than Services prices in general? Yes, but the difference in annualized price increases was typically smaller than one percentage point except in 2002 and 2010, when recession’s aftermath depressed other services prices more than (heavily-subsidized) medical care prices. Recessions’ impact on commodity prices pushed the year-to-year overall CPI below zero at times, which underscores the inaptness of comparing prices of medical or educational services to any price index such as the CPI which is heavily weighted by goods.

In other words, living longer doesn’t increase health care spending so much as it delays the large amount spent near death. Some health care spending is associated with those intervening, relatively healthy years, just not much compared with that spent in one’s final years.Living longer offers many benefits. That it isn’t, by itself, a major contributor to health care spending is a nice bonus.

Fiscal imbalances predating the Great Recession but aggravated by it prompted the U.S. Congress to enact in 2011 legislation that, in the absence of other measures, would trigger two years later a so-called “budget sequestration” procedure that implied reducing government discretionary spending to unprecedented low levels over the following decade. For that reason, economic agents may not have expected this “fiscal stabilization measure of last resort” to be sustainable when it was put into effect in 2013 as scheduled. This is exactly the issue this paper set out to explore, on the grounds that sizing up the expectations that economic agents had about the budget sequestration can provide powerful insights on how fiscal stabilization is likely to proceed in the U.S., going forward. The paper makes inferences about the credibility enjoyed by the budget sequestration with an adapted version of the Business Cycle Accounting approach, originally developed for other purposes.

The main finding is that the evidence favors a scenario in which spending cuts are half the size of those actually implied by the sequester. The paper takes this result as an indication that the U.S. is unlikely to address its unresolved fiscal imbalances with just spending austerity, an interpretation consistent with existing literature that traces the seemingly anomalous behavior of economic variables during the Great Recession and its aftermath to alternative fiscal stabilization mechanisms.

Medical innovations have improved survival and treatment for many diseases but have simultaneously raised spending on health care. Many health economists believe that technological change is the major factor driving the growth of the heath care sector. Whether quality has increased as much as spending is a central question for both positive and normative analysis of this sector. This is a question of the impact of new innovations on quality-adjusted prices in health care. We preform a systematic analysis of the impact of technological change on quality-adjusted prices, with over six thousand comparisons of innovations to incumbent technologies. For each innovation in our dataset, we observe its price and quality, as well as the price and quality of an incumbent technology treating the same disease. Our main finding is that an innovation’s quality-adjusted prices is higher than the incumbent’s for about two-thirds (68%) of innovations. Despite this finding, we argue that quality-adjusted prices may fall or rise over time depending on how fast prices decline for a given treatment over time. We calibrate that price declines of 4% between the time when a treatment is a new innovation and the time when it has become the incumbent would be sufficient to offset the observed price difference between innovators and incumbents for a majority of indications. Using standard duopoly models of price competition for differentiated products, we analyze and assess empirically the conditions under which quality-adjusted prices will be higher for innovators than incumbents. We conclude by discussing the conditions particular to the health care industry that may result in less rapid declines, or even increases, in quality-adjusted prices over time.

Our simulations show that a primary driver of long-term fiscal challenges for the state and local government sector continues to be the growth in health-related costs. Specifically, state and local Medicaid expenditures and the cost of health care compensation for state and local government employees and retirees generally grow at a rate that exceeds GDP.7 The model’s simulations suggest that the sector’s health-related costs will be about 4.1 percent of GDP in 2016 and 6.3 percent of GDP in 2065. From 2016 through 2065, Medicaid expenditures are expected to increase on average by 0.5 percentage points more than GDP—referred to as excess cost growth. Other health related receipts and expenditures, including health care compensation for state and local government employees and retirees, are expected to increase on average by 0.9 percentage points more than GDP each year from 2016 to 2023, and then begin to decline, reaching 0.7 percentage points in 2065.

This paper proposes a practical way for ex-post indexing of level premiums in lifelong medical insurance contracts, in order to take into account observed medical inflation. We show that ex-post indexing can be achieved by considering only premiums, without explicit reference to reserves. This appears to be relevant in practice as reserving mechanisms may not be transparent to policyholders and as some insurers do not compute contract-specific reserves, managing the whole portfolio in a collective way. The present study originates from a proposal for indexing lifelong medical insurance level premiums in Belgium. As an application, we study the impact of various indexing mechanisms on a typical medical insurance portfolio on the Belgian market.

Over the past five decades, broad changes in the US health care system have dramatically influenced growth in health care expenditures. This review identifies the salient factors driving the growth of medical expenditures and how they influenced the trajectory of health economics research. We find that the research identified — and was strongly influenced by — four eras of expenditure growth: period 1, coverage expansion; period 2, experimentation with financial incentives; period 3, the managed care backlash; and period 4, a golden era of declining expenditure growth. We conclude by discussing some themes from this research suggesting optimism that, going forward, we can curb excess expenditure growth above GDP growth without harming population health.